Sleep period dividing method and device
A sleep stage and state signal technology, applied in the information field, can solve the problems of low accuracy and high computational complexity, and achieve the effect of less computational complexity, low computational complexity, and guaranteed accuracy
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[0147] Such as Figure 4 As shown, this example provides an intelligent judgment method for sleep stages, including:
[0148] First, obtain the signal source, where the signal source includes EEG signal, EOG eye movement signal and EMG signal.
[0149] Secondly, signal preprocessing, the preprocessing here includes amplitude threshold filtering in time domain, wavelet threshold filtering in frequency domain, and de-artifacting of oculoelectricity and myoelectricity.
[0150] Again, feature extraction is performed on the preprocessed signal. The feature extraction here can use the Hjorth parameter to extract time-domain features, extract time-frequency domain features and extract nonlinear features. The time-frequency domain features here include at least: frequency band energy ratio; the nonlinear features at least include sample entropy.
[0151] Finally, sleep stages are identified. In this example, multi-connection rules and SVM model are used for identification. Before ...
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